Una candidatura hecha para este puesto de trabajo — un currículum y una carta de presentación adaptados que responden directamente a la oferta.
Leyton is building an AI-native product team in Barcelona to own end-to-end products for real businesses across multiple countries. You would sit with users, gather needs, and define precise specifications that engineers and agents can turn into working software.
The role emphasizes inclusion of acceptance criteria, measurable outcomes, and true ownership of the product lifecycle. You will join a growing team at Mainloop Barcelona, with travel to meet users, and a strong focus on delivering
Product Owner
Own the product, not the ticket queue — the business relationship, the backlog, acceptance, and whether the thing actually gets used.
Mainloop is a new engineering team inside an established international group. We are in Barcelona, we are being built from scratch this year, and we have the backing, the customers and the product portfolio of a company that has been around for decades. You get the interesting part of a new team without the part where you check whether payroll clears.
Two more things about where this comes from and where it goes. The group has been running a techlab in Casablanca for more than eight years — Barcelona is its second, built to sit closer to the teams we build for, and AI-native from the first commit, because it starts from a blank page. And the plan does not stop at internal work: within about a year and a half we intend to externalise — external clients, our products sold on the market, products developed for it. The first eighteen months are deliberately spent building as much as possible for the group while the machine gets set up. You would arrive at the start of that curve, not after it.
What we build is the software that automates professional-services work — across roughly fifteen countries, for businesses drowning in administration: the forms, the approvals, the reconciliations, the spreadsheet somebody rebuilds every month. We work in two halves. One half goes into a business, finds out what really happens there, and proves fast whether an idea is worth having. The other half — your half — takes what is proven and owns it for years: gathers the needs, keeps building, gets it adopted, and makes sure it stays worth having. Most automation teams stop at the demo. The entire point of ours is that we do not.
We are not looking for a backlog administrator. If your last role was turning other people's decisions into tickets and running the ceremonies around them, this is a different job. Here you are the product manager and the product owner: there is no one above you writing the strategy for your products, and no one below you writing the stories. What should exist, in what order, and whether what shipped is right — that is yours.
What the job actually is
A product arrives with a handover pack — already proven with its stakeholders by the first half of the team, already hardened for production. From day one it belongs to you and one developer, as a pair, for its life.
Why this job exists — the honest version
Here is the thing our industry has just learned, and it is the reason we are hiring you: AI made building fast, and it did not make building the right thing any more likely. Surveys now find most companies shipping faster with AI while almost none can point to the return. It has never been easier to run, at speed, in the wrong direction.
In a team like ours the engineers steer agents, and implementation is rarely the bottleneck. The bottleneck is deciding — what to build, for whom, in what order, and whether what shipped actually did what the business needed. That is not a job the agents do. It is this job, and in an AI-native team it is a more senior, more consequential job than the same title has ever been — because every decision you write down gets built, quickly, exactly as you wrote it.
What stays yours, permanently:
You will define how the PO role works here
You are the first. That is not a gap in the org chart — it is the offer.
How product ownership works in an AI-native team is a genuinely open question in our industry right now, and the honest answer is that nobody's playbook fits yet. Ours will be written here, over your first year, by you and Edouard together: how needs become specs, how acceptance works when agents build, how adoption gets measured, how many products one pair can carry. The POs we hire after you will be onboarded onto the way you built.
If you have ever read a process document and thought I could have written this better — this is the job where you get to.
You will get seriously good at building with AI
We are an AI-native team, genuinely — not a team that added a Copilot licence. Everyone gets their own Claude Max subscription and the tooling to use it properly, and that includes you. The product people we admire in this market prototype with AI before they ask anyone to build: a rough working version of an idea, made in an afternoon, shown to a stakeholder — because a prototype communicates intent better than any document, and because it kills bad ideas cheaply. You will learn to do that here if you cannot already, and you will learn what makes a specification one an agent builds correctly the first time. That skill is being repriced upward across our entire industry, and this is one of very few jobs where you would practise it daily on products people depend on.
Mainloop Barcelona certificate
Something we are building alongside the team, and we think it is genuinely unusual.
Over your first two to three years here you work through a defined body of knowledge — how we build, how we run products, how a need becomes a spec becomes working, adopted software — and when you can demonstrably run a product our way, you are awarded the Mainloop Barcelona certificate. It is yours: it goes on your CV, and we intend to make it mean something in this market.
How we build
Every product starts from the same scaffold, and it is the same in most of our repos — deliberately. For you that is the whole point: every product in your portfolio has the same shape, so carrying several does not mean holding several different worlds in your head. It also means the handover pack you inherit from the first half of the team actually tells you how the thing works — because it is built the way everything else is built.
You do not need to arrive knowing our tooling, and this ad deliberately lists no technologies. You need to be technical enough to hold your own in an engineering discussion, and to read what an agent produced closely enough to judge it. The rest — our architecture, our patterns, our method — is what we train you on.
Things worth knowing up front
If you would be moving to Barcelona for this
We do not expect you to absorb the cost of relocating, and we would rather say what we cover than leave you to ask.
Three things here are worth more than they look on an offer comparison, particularly against a US one:
If you are coming from the United States
two things are usually worth more than the headline salary gap and almost nobody has done the arithmetic: a salary here can sit below the Foreign Earned Income Exclusion, and federal student loans on an income-driven plan are assessed on the income that exclusion has already removed. We are not your tax advisor and you should get one — but ask in the first conversation and we will walk you through the comparison we ran, including the parts where the number comes out smaller.
What we are looking for
One bar sits above everything else, so here it is plainly. You can own a product end to end — the need, the decision, the specification, the acceptance, the outcome — and you are technical enough to contribute to an engineering discussion and to judge what an AI agent built. You do not need to code for a living. You do need to have no fear of the inside of the machine. If you read that and thought that is the job I want, keep reading.
Read the rest as a description of the person